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  1. Stackups
  2. Application & Data
  3. Relational Databases
  4. Postgresql As A Service
  5. Heroku Postgres vs Pouchdb

Heroku Postgres vs Pouchdb

OverviewDecisionsComparisonAlternatives

Overview

Heroku Postgres
Heroku Postgres
Stacks607
Followers314
Votes38
Pouchdb
Pouchdb
Stacks148
Followers242
Votes6
GitHub Stars17.5K
Forks1.5K

Heroku Postgres vs Pouchdb: What are the differences?

Developers describe Heroku Postgres as "Heroku's Database-as-a-Service. Based on the most powerful open-source database, PostgreSQL". Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management. On the other hand, Pouchdb is detailed as "Open-source JavaScript database inspired by Apache CouchDB that's designed to run well within the browser". PouchDB enables applications to store data locally while offline, then synchronize it with CouchDB and compatible servers when the application is back online, keeping the user's data in sync no matter where they next login.

Heroku Postgres and Pouchdb are primarily classified as "PostgreSQL as a Service" and "Databases" tools respectively.

Some of the features offered by Heroku Postgres are:

  • High Availability
  • Rollback
  • Dataclips

On the other hand, Pouchdb provides the following key features:

  • Cross browser compatibility
  • Lightweight
  • Easy to learn

Pouchdb is an open source tool with 12.1K GitHub stars and 1.2K GitHub forks. Here's a link to Pouchdb's open source repository on GitHub.

According to the StackShare community, Heroku Postgres has a broader approval, being mentioned in 74 company stacks & 38 developers stacks; compared to Pouchdb, which is listed in 8 company stacks and 9 developer stacks.

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Advice on Heroku Postgres, Pouchdb

Jorge
Jorge

Jan 15, 2020

Needs advice

Considering moving part of our PostgreSQL database infrastructure to the cloud, however, not quite sure between AWS, Heroku, Azure and Google cloud. Things to consider: The main reason is for backing up and centralize all our data in the cloud. With that in mind the main elements are: -Pricing for storage. -Small team. -No need for high throughput. -Support for docker swarm and Kubernetes.

51.8k views51.8k
Comments

Detailed Comparison

Heroku Postgres
Heroku Postgres
Pouchdb
Pouchdb

Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.

PouchDB enables applications to store data locally while offline, then synchronize it with CouchDB and compatible servers when the application is back online, keeping the user's data in sync no matter where they next login.

High Availability;Rollback;Dataclips;Automated Health Checks
Cross browser compatibility; Lightweight; Easy to learn; Open source
Statistics
GitHub Stars
-
GitHub Stars
17.5K
GitHub Forks
-
GitHub Forks
1.5K
Stacks
607
Stacks
148
Followers
314
Followers
242
Votes
38
Votes
6
Pros & Cons
Pros
  • 29
    Easy to setup
  • 3
    Follower databases
  • 3
    Dataclips for sharing queries
  • 3
    Extremely reliable
Cons
  • 2
    Super expensive
Pros
  • 2
    Offline cache
  • 1
    Repication
  • 1
    Free
  • 1
    Very fast
  • 1
    JSON
Integrations
PostgreSQL
PostgreSQL
Heroku
Heroku
No integrations available

What are some alternatives to Heroku Postgres, Pouchdb?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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